Abstract:

Aimed at the uncertain factors in unmanned combat aerial vehicle (UCAV) air-to-surface combat, an online real-time attacking trajectory planning algorithm based on the receding horizon control (RHC) optimize strategy and Gauss pseudospectral method (GPM) is presented. The proposed algorithm adopts RHC strategy which transforms the global planning model into a series of overlapping but moving forward local optimize window, uncertain error can be eliminated through rolling update and feedback revise of this strategy, computational complexity and computational resource need can be greatly reduced through model predictive of this strategy; GPM is adopted to resolve a high-fidelity attacking trajectory which combines the flight envelop constraints, weapon delivery constraints and threat avoidance constraints; real-time iteration scheme is adopted to give initial Guess, and auto switch objective function is adopted to guide UCAV evade pop-up threat. Simulation result shows that the proposed algorithm can greatly eliminate uncertain error, and get a high-fidelity attacking trajectory in real time.